Schema Design

Schema Design
Software Engineer, MongoDB
Craig Wilson
#MongoDBDays
@craiggwilson

All application development is
Schema Design

Success comes from a
Proper Data Structure

Terminology
RDBMS MongoDB
Database ➜ Database
Table ➜ Collection
Row ➜ Document
Index ➜ Index
Join ➜ Embedding & Linking

{
_id: “123”,
title: "MongoDB: The Definitive Guide",
authors: [
{ _id: "kchodorow", name: "Kristina Chodorow“ },
{ _id: "mdirold", name: “Mike Dirolf“ }
],
published_date: ISODate("2010-09-24"),
pages: 216,
language: "English",
publisher: {
name: "O’Reilly Media",
founded: "1980",
location: "CA"
}
}
What is a Document?

Traditional Schema Design
Focus on Data Storage

Document Schema Design
Focus on Data Usage

Traditional Schema Design
What answers do I have?

Document Schema Design
What questions do I
have?

Library Management Application
• Patrons/Users
• Books
• Authors
• Publishers

Question:
What is a Patron’s
Address?

> patron = db.patrons.find({ _id : “joe” })
{
_id: "joe“,
name: "Joe Bookreader”
}
> address = db.addresses.find({ _id : “joe” })
{
_id: "joe“,
street: "123 Fake St. ",
city: "Faketon",
state: "MA",
zip: 12345
}
A Patron and their Address

{
_id: "joe",
name: "Joe Bookreader",
address: {
street: "123 Fake St. ",
city: "Faketon",
state: "MA",
zip: 12345
}
}
A Patron and their Address

One-to-One Relationships
• “Belongs to” relationships are often embedded.
• Holistic representation of entities with their
embedded attributes and relationships.
• Optimized for read performance

Question:
What are a Patron’s
Addresses?

> patron = db.patrons.find({ _id : “bob” })
{
_id: “bob",
name: “Bob Knowitall",
addresses: [
{street: "1 Vernon St.", city: "Newton", …},
{street: "52 Main St.", city: "Boston", …},
]
}
A Patron and their Addresses

> patron = db.patrons.find({ _id : “bob” })
{
_id: “bob",
name: “Bob Knowitall",
addresses: [
{street: "1 Vernon St.", city: "Newton", …},
{street: "52 Main St.", city: "Boston", …},
]
}
{
_id: "joe",
name: "Joe Bookreader",
address: { street: "123 Fake St. ", city: "Faketon", …}
}
A Patron and their Addresses

Migration Possibilities
• Migrate all documents when the schema changes.
• Migrate On-Demand
– As we pull up a patron’s document, we make the change.
– Any patrons that never come into the library never get
updated.
• Leave it alone
– As long as the application knows about both types…

Question:
Who is the publisher of
this book?

Book
MongoDB: The Definitive Guide,
By Kristina Chodorow and Mike Dirolf
Published: 9/24/2010
Pages: 216
Language: English
Publisher: O’Reilly Media, CA

> book = db.books.find({ _id : “123” })
{
_id: “123”,
authors: [ "Kristina Chodorow", "Mike Dirolf" ],
pages: 216,
language: "English",
publisher: {
founded: "1980",
location: "CA"
}
}
Book with embedded Publisher

Book with embedded Publisher
• Optimized for read performance of Books
• Other queries become difficult

Question:
Who are all the
publishers in the
system?

> publishers = db.publishers.find()
{
_id: “oreilly”,
founded: "1980",
location: "CA"
}
{
_id: “penguin”,
name: “Penguin”,
founded: “1983”,
location: “CA”
}
All Publishers

> book = db.books.find({ _id: “123” })
{
_id: “123”,
publisher_id: “oreilly”,
authors: [ "Kristina Chodorow", "Mike Dirolf" ],
pages: 216,
language: "English"
}
> db.publishers.find({ _id : book.publisher_id })
{
_id: “oreilly”,
founded: "1980",
location: "CA"
}
Book with linked Publisher

Question:
What are all the books a
publisher has
published?

> publisher = db.publishers.find({ _id : “oreilly” })
{
_id: “oreilly”,
founded: "1980",
location: "CA“,
books: [“123”,…]
}
> books = db.books.find({ _id: { $in : publisher.books } })
Publisher with linked Books

Question:
Who are the authors of a
given book?

{
_id: “123”,
pages: 216,
language: "English“,
authors: [“kchodorow”, “mdirolf”]
}
> authors = db.authors.find({ _id : { $in : book.authors } })
{ _id: "kchodorow", name: "Kristina Chodorow”, hometown: … }
{ _id: “mdirolf", name: “Mike Dirolf“, hometown: … }
Books with linked Authors

{
_id: “123”,
pages: 216,
language: "English“,
authors: [
{ id: "kchodorow", name: "Kristina Chodorow” },
{ id: "mdirolf", name: "Mike Dirolf” }
]
}
Books with linked Authors

Question:
What are all the books
an author has written?

> authors = db.authors.find({ _id : “kchodorow” })
{
_id: "kchodorow",
name: "Kristina Chodorow",
hometown: "Cincinnati",
books: [ {id: “123”, title : "MongoDB: The Definitive Guide“ } ]
}
Authors with linked Books

> authors = db.authors.find({ _id : “kchodorow” })
{
_id: "kchodorow",
name: "Kristina Chodorow",
hometown: "Cincinnati",
books: [ {id: “123”, title : "MongoDB: The Definitive Guide“ } ]
}
{
_id: “123”,
authors: [
{ id: "kchodorow", name: "Kristina Chodorow” },
{ id: "mdirolf", name: "Mike Dirolf” }
]
}
Links on both Authors and Books

Linking vs. Embedding
• Embedding
– Great for read performance
– Writes can be slow
– Data integrity needs to be managed
• Linking
– Flexible
– Data integrity is built-in
– Work is done during reads

Question:
What are all the books
about databases?

{
_id: “123”,
category: “MongoDB”
}
> categories = db.categories.find({ _id: “MongoDB” })
{
_id: “MongoDB”,
parent: “Databases”
}
Categories as Documents

{
_id: “123”,
categories: [“MongoDB”, “Databases”, “Programming”]
}
> db.books.find({ categories: “Databases” })
Categories as an Array

{
_id: “123”,
category: “Programming/Databases/MongoDB”
}
> db.books.find({ category: ^Programming/Databases/* })
Categories as a Path

Conclusion
• Schema design is different in MongoDB
• Basic data design principals stay the same
• Focus on how an application accesses/manipulates
data
• Evolve the schema to meet requirements as they
change

Schema Design
Software Engineer, 10gen
Craig Wilson
#MongoDBDays
@craiggwilson

Schema Design

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